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Advances in intelligent and soft computing

The present research paper is based upon the blend chest process pertaining to the paper making mill. There is always a requirement of controlling the outputs of multiple units involved in paper making like blend chest, headbox, wire, press section, dryer, calender, and reel unit. The final output is good quality paper rolls. To achieve this control, automatic feedback controllers are employed in paper mills. In this work, 2 different optimization algorithm viz. Simulated Annealing (SA) and Genetic Algorithm (GA) have been utilized to develop the control system using the MATLAB for monitoring of the blend chest process. At the end, the performance comparison of the developed control systems is performed. 

Design of SA and GA Optimized PID Controllers for Controlling Blend Chest Level of Paper Mill

This article presents a reference design for the well-known ball-on-beam laboratory experiment, where a spherical ball without direct actuation is only balanced by the inclination of a supporting structure, such as beam, rail or tube. The design introduced here is completely open-source and utilizes only a handful of off-the-shelf components and 3D printing; resulting in an exceptionally low hardware cost. Moreover, the resulting apparatus fits on a standard expansion module format, known as a Shield, which is compatible with a range of microcontroller prototyping boards from the Arduino ecosystem. This affordable, small, reproducible and open design is thus intended to aid control systems or mechatronics education via hands-on student experiments or even conducting research on a budget. In addition to the hardware design with downloadable project files, we also present an application programming interface and the results of a demonstration example here.

BOBShield: An Open-Source Miniature “Ball and Beam” Device for Control Engineering Education

The present research paper is based upon the blend chest process pertaining to the paper making mill. There is always a requirement of controlling the outputs of multiple units involved in paper making like blend chest, headbox, wire, press section, dryer, calender, and reel unit. The final output is good quality paper rolls. To achieve this control, automatic feedback controllers are employed in paper mills. In this work, 2 different optimization algorithm viz. Simulated Annealing (SA) and Genetic Algorithm (GA) have been utilized to develop the control system using the MATLAB for monitoring of the blend chest process. At the end, the performance comparison of the developed control systems is performed.

Tuning a controller for any process purely depends on the process dynamics. Improper selection of controller parameters could spoil the entire design. Selecting a tuning technique to achieve a desired response could be dealt as an optimization problem. This paper deals with the tuning of a fuzzy logic controller using Simulated Annealing to minimize the Mean Square Error between the desired and actual output of a nonlinear system. The proposed algorithm is tested on a real time ball beam system and the results are compared with the simulated responses. By using this method best results are obtained by using less number of fuzzy membership functions.

https://ieeexplore.ieee.org/iel7/7045158/7054731/07054808.pdf

Tuning and implementation of fuzzy logic controller using simulated annealing in a nonlinear real-time system

This project proposes a novel low cost approach to gesture recognition using neural networks for end user applications control in contrary to more expensive devices prevalent in the market. The final outcome is proposed to be a versatile product with variety of applications which can cater to many user needs. In fact, a person with minimal programming knowledge can design an application with the proposed and prototyped device. The use of neural networks has made this possible, as the pattern recognition of neural networks is highly accurate than conventional programming.

S. Tharun Kumar

Papers

Tuning and implementation of fuzzy logic controller using simulated annealing in a nonlinear real-time system

Low-Cost Gesture Detector Using Neural Networks